Protein nitration and nitrosylation are essential post-translational modifications (PTMs) involved in many fundamental cellular processes. Recent studies have revealed that excessive levels of nitration and nitrosylation in some critical proteins are linked to numerous chronic diseases. Therefore, the identification of substrates that undergo such modifications in a site-specific manner is an important research topic in the community and will provide candidates for targeted therapy. In this study, we aimed to develop a computational tool for predicting nitration and nitrosylation sites in proteins. We first constructed four types of encoding features, including positional amino acid distributions, sequence contextual dependencies, physicochemical properties, and position-specific scoring features, to represent the modified residues. Based on these encoding features, we established a predictor called DeepNitro using deep learning methods for predicting protein nitration and nitrosylation. Using n-fold cross-validation, our evaluation shows great AUC values for DeepNitro, 0.65 for tyrosine nitration, 0.80 for tryptophan nitration, and 0.70 for cysteine nitrosylation, respectively, demonstrating the robustness and reliability of our tool. Also, when tested in the independent dataset, DeepNitro is substantially superior to other similar tools with a 7%-42% improvement in the prediction performance. Taken together, the application of deep learning method and novel encoding schemes, especially the position-specific scoring feature, greatly improves the accuracy of nitration and nitrosylation site prediction and may facilitate the prediction of other PTM sites. DeepNitro is implemented in JAVA and PHP and is freely available for academic research at http://deepnitro.renlab.org.
Amino Acid Sequence ; Amino Acids ; metabolism ; Deep Learning ; Humans ; Internet ; Neural Networks (Computer) ; Nitrosation ; Proteins ; chemistry ; metabolism ; Reproducibility of Results ; Software

Redox signal transduction, especially the oxidative modification of proein thiols, correlates with many diseases and becomes an expanding research area. However, there was rare method for quick and specific detection of protein thiols and their oxidative modification in living cells. In this article, we review the current chemical strategies for the detection and quantification of protein thiols and related cysteine oxidation. We also look into the future of the development of fluorescent probes for protein thiols and their potential application in the research of reactive cysteine proteomes and early detection of redox-related diseases.
Animals ; Cysteine ; metabolism ; Fluorescent Dyes ; Humans ; Nitrosation ; Oxidation-Reduction ; Proteins ; chemistry ; metabolism ; Reactive Nitrogen Species ; metabolism ; Reactive Oxygen Species ; metabolism ; Sulfenic Acids ; analysis ; Sulfhydryl Compounds ; analysis ; chemistry ; metabolism

S-Nitros(yl)ation is a ubiquitous redox-based post-translational modification of protein cysteine thiols by nitric oxide or its derivatives, which transduces the bioactivity of nitric oxide (NO) by regulation of protein conformation, activity, stability, localization and protein-protein interactions. These years, more and more S-nitrosated proteins were identified in physiological and pathological processes and the number is still growing. Here we developed a database named SNObase ( http://www.nitrosation.org ), which collected S-nitrosation targets extracted from literatures up to June 1st, 2012. SNObase contained 2561 instances, and provided information about S-nitrosation targets, sites, biological model, related diseases, trends of S-nitrosation level and effects of S-nitrosation on protein function. With SNObase, we did functional analysis for all the SNO targets: In the gene ontology (GO) biological process category, some processes were discovered to be related to S-nitrosation ("response to drug", "regulation of cell motion") besides the previously reported related processes. In the GO cellular component category, cytosol and mitochondrion were both enriched. From the KEGG pathway enrichment results, we found SNO targets were enriched in different diseases, which suggests possible significant roles of S-nitrosation in the progress of these diseases. This SNObase means to be a database with precise, comprehensive and easily accessible information, an environment to help researchers integrate data with comparison and relevancy analysis between different groups or works, and also an SNO knowledgebase offering feasibility for systemic and global analysis of S-nitrosation in interdisciplinary studies.
Animals ; Binding Sites ; Databases, Protein ; Disease ; Humans ; Internet ; Mice ; Models, Molecular ; Nitrosation ; Protein Processing, Post-Translational ; Proteins ; chemistry ; metabolism ; Rats ; Software ; Sulfur ; metabolism

In this study we developed a quantitative proteomic method named ICAT switch by introducing isotope-coded affinity tag (ICAT) reagents into the biotin-switch method, and used it to investigate S-nitrosation in the liver of normal control C57BL/6J mice and type 2 diabetic KK-Ay mice. We got fifty-eight S-nitrosated peptides with quantitative information in our research, among which thirty-seven had changed S-nitrosation levels in diabetic mouse liver. The S-nitrosated peptides belonged to forty-eight proteins (twenty-eight were new S-nitrosated proteins), some of which were new targets of S-nitrosation and known to be related with diabetes. S-nitrosation patterns were different between diabetic and normal mice. Gene ontology enrichment results suggested that S-nitrosated proteins are more abundant in amino acid metabolic processes. The network constructed for S-nitrosated proteins by text-mining technology provided clues about the relationship between S-nitrosation and type 2 diabetes. Our work provides a new approach for quantifying S-nitrosated proteins and suggests that the integrative functions of S-nitrosation may take part in pathophysiological processes of type 2 diabetes.
Amino Acid Sequence ; Animals ; Computational Biology ; Diabetes Mellitus, Experimental ; metabolism ; pathology ; Female ; Isotope Labeling ; Liver ; chemistry ; pathology ; Mice ; Mice, Inbred C57BL ; Molecular Sequence Data ; Nitrosation ; Peptides ; analysis ; Proteome ; chemistry

OBJECTIVETo observe the effect of Radix Ginseng and Radix Ophiopogonis extract (SMF) on protein S-nitrosylation in rats myocardial with ischemia/reperfusion injury (MI/RI).

METHODMyocardial ischemia/reperfusion in rats were produced by occlusion of the left anterior descending coronary artery. To study the cardioprotective effects of SMF on the acute MI/RI rats, the serum levels of creatine kinase (CK), lactate dehydrogenase (LDH), and nitric oxide (NO) were determined. The change of the expression of endothelial nitric oxide synthase (eNOS) was detected by Western blot. The content of related S-nitrosylation proteins in myocardial tissue was measured by Biotin-Switch method.

RESULTSMF significantly decreased the serum levels of CK and LDH as well as increased the serum levels of NO and the expression of eNOS in myocardial tissue. The contents of S-nitrosylation proteins were significantly increased from (4.42 +/- 0.60) micromol x g(-1) to (8.78 +/- 1.37) micromol x g(-1). The molecular weight of the majority S-nitrosylation proteins were in the range of 90 x 10(3)-117 x 10(3).

CONCLUSIONIncreased expression of eNOS and NO induced by SMF may activate S-nitrosylation of many proteins in rat hearts. The change of the activities or functions of those proteins by S-nitrosylation may be an important mechanism for myocardial protective effects of SMF.

Animals ; Blotting, Western ; Creatine Kinase ; blood ; Drugs, Chinese Herbal ; pharmacology ; L-Lactate Dehydrogenase ; blood ; Male ; Myocardial Ischemia ; blood ; drug therapy ; metabolism ; Myocardium ; metabolism ; Nitric Oxide ; blood ; Nitric Oxide Synthase Type III ; metabolism ; Nitrosation ; drug effects ; Nitroso Compounds ; metabolism ; Panax ; chemistry ; Random Allocation ; Rats ; Rats, Sprague-Dawley

BACKGROUND: Stomach cancer is the most malignant neoplasm among Koreans. There ane a number of epidemiological studies on dietary factors of stomach cancer in many countries. However, analytical studies on Korean dietary factors are very scarce. SUBJECTS AND METHODS: A case-control study was conducted at the Korea Cancer Center Hospital in Seoul between April and September in 1996. One hundred twenty-six stomach cancer patients confirmed by the histological diagnosis were compared with 234 control subjects matched by age, sex, and admission date. A food frequency questionnaire asking the consumption frequency of 85 selected food items was used to gather the information from all subjects via a face-to-face interview. Multiple logistic regression models were used to estimate relative risks when controlling simultaneously for covariates. RESULTS: An increased risk of stomach cancer was noted among those with low economic status, fast eating rate, high eating out, hot-temperature soup preference, salt preference, cucumber Kimchi intake, use of pickled fish in Kimchi. Intake of garlic, green onion, tofu, mung bean pancake, acorn-starch paste, starch vermicelli with mixed vegetables, total fruits, citrus fruits, cabbage, green peppers, spinach, mushrooms and total meat appeared to be protective. Stomach cancer risk was not associated with intake of rice, dairy product, fishes, condiments, coffee, tea, and the cooking methods. These data suggested that the high intake of salt and smoked or pickled food may be associated with a hig risk of stomach cancer, and this association could be due to a intragastric formation of nitrosamines. The negative association with fruits and some vegetable consumption may be due to the inhibition of nitrosation process. CONCLUSION: Our findings indicated that dietary factors contributed to stomach cancer occurrence in Korea, and this may offer clues for further ethnical and prevention research.
Agaricales ; Brassica ; Capsicum ; Case-Control Studies ; Citrus ; Coffee ; Condiments ; Cooking ; Dairy Products ; Diagnosis ; Diet ; Eating ; Epidemiologic Studies ; Fishes ; Fruit ; Garlic ; Humans ; Korea ; Logistic Models ; Meat ; Nitrosamines ; Nitrosation ; Onions ; Seoul ; Smoke ; Soy Foods ; Spinacia oleracea ; Starch ; Stomach Neoplasms* ; Stomach* ; Tea ; Vegetables ; Surveys and Questionnaires